Claude Skills Deep Dive: Best Practices from skill-creator

skill-creator is one of the most important example skills in the Anthropic repository. It provides a complete framework for creating, packaging, and iterating on Claude skills. This article will dissect its structure, analyze its design principles, and extract best practices you can apply to your own skill development.

What is skill-creator?

skill-creator is a meta-skill—a skill that helps create other skills. It transforms Claude from a general-purpose assistant into a specialized skill development coach equipped with:

• Specialized workflows: 6-step process for skill creation
• Tool integrations: Scripts for initialization and packaging
• Domain expertise: Best practices for skill design
• Bundled resources: Python scripts and validation tools

Core Value Proposition

Instead of manually writing SKILL.md files and organizing directories, skill-creator provides a systematic approach that ensures consistency, quality, and efficiency across all your skills.

Anatomy of the Skill

The skill-creator demonstrates the standard structure that all well-designed skills should follow:

skill-creator/
├── SKILL.md (required)
│   ├── YAML frontmatter metadata
│   └── Markdown instructions
└── Bundled Resources (optional)
    ├── scripts/
    │   ├── init_skill.py
    │   └── package_skill.py
    └── LICENSE.txt

SKILL.md Structure

Every skill starts with its metadata in YAML frontmatter:

---
name: skill-creator
description: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
license: Complete terms in LICENSE.txt
---

Bundled Resources Analysis

Scripts Directory (scripts/)

skill-creator includes two essential Python scripts that make skill creation efficient and reliable.

init_skill.py

Purpose: Generate a complete skill template with proper structure

Usage:

scripts/init_skill.py <skill-name> --path <output-directory>

What it does:

1. Creates the skill directory at the specified path
2. Generates SKILL.md template with proper frontmatter and TODO placeholders
3. Creates empty resource directories: scripts/, references/, and assets/
4. Adds example files that can be customized or deleted

Key Benefits:

• Consistency: Every skill starts with the same structure
• Efficiency: No manual directory creation or file templating
• Reliability: Follows Anthropic's best practices automatically

package_skill.py

Purpose: Validate and package a skill into a distributable zip file

Usage:

scripts/package_skill.py <path/to/skill-folder>

# Optional: specify output directory
scripts/package_skill.py <path/to/skill-folder> ./dist

Validation checks:

1. YAML frontmatter format: Required fields (name, description)
2. Skill naming conventions: Proper directory structure
3. Description quality: Completeness and specificity
4. File organization: Proper resource references

Packaging Process:

• Creates a zip file named after the skill (e.g., my-skill.zip)
• Maintains proper directory structure for distribution
• Only packages if validation passes

When to Include Bundled Resources

Not every skill needs all three resource types. Here's when to use each:

Progressive Disclosure Design Principle

One of skill-creator's most important contributions is the progressive disclosure pattern—a three-level loading system that manages context efficiently:

Level 1: Metadata (Always in Context)

Content: name and description from YAML frontmatter

Size: ~100 words

When loaded: Always in Claude's context window

Purpose: Determines when to trigger the skill

Level 2: SKILL.md Body (When Triggered)

Content: Complete instructions and workflows

Size: <5k words (recommended)

When loaded: Only when skill is triggered by user query

Purpose: Provides procedural knowledge for task execution

Level 3: Bundled Resources (As Needed)

Content: Scripts, references, assets

Size: Unlimited (scripts can execute without reading into context)

When loaded: Only when Claude determines they're needed

Purpose: Provides detailed reference material without hogging context window

The 6-Step Skill Creation Process

skill-creator provides a complete workflow that transforms skill ideas into production-ready packages.

Step 1: Understanding with Concrete Examples

Purpose: Clearly understand how the skill will be used in practice

Questions to ask users:

• "What functionality should this skill support?"
• "Can you give specific examples of how this skill would be used?"
• "What would a user say that should trigger this skill?"

Example: For an image-editor skill, ask about specific use cases like "Remove red-eye" or "Rotate this image".

Output: Clear sense of functionality the skill should support

Step 2: Planning Reusable Skill Contents

Purpose: Identify which resources would make repeated workflows more efficient

Analysis process:

1. Consider how to execute each example from scratch
2. Identify what scripts, references, and assets would be helpful when repeating these workflows

Examples:

PDF Editor Skill:

• Example query: "Help me rotate this PDF"
• Reusable resource: scripts/rotate_pdf.py
• Why: Code would be rewritten repeatedly without the script

Frontend Builder Skill:

• Example query: "Build me a todo app"
• Reusable resource: assets/hello-world/ template
• Why: Same boilerplate HTML/React needed each time

BigQuery Skill:

• Example query: "How many users logged in today?"
• Reusable resource: references/schema.md
• Why: Table schemas and relationships would be rediscovered each time

Output: List of reusable resources (scripts, references, assets) to include

Step 3: Initializing the Skill

Purpose: Create the skill directory structure using automation

When to skip: Only if the skill already exists and needs iteration or packaging

Command:

scripts/init_skill.py <skill-name> --path <output-directory>

What the script creates:

• Skill directory at specified path
• SKILL.md template with proper frontmatter and TODO placeholders
• Empty resource directories: scripts/, references/, assets/
• Example files that can be customized or deleted

Step 4: Editing the Skill

Purpose: Transform the template into a production-ready skill

Key mindset: Write for another Claude instance. Focus on information that would be beneficial and non-obvious.

Start with bundled resources:

1. Implement scripts, references, and assets identified in Step 2
2. Delete example files not needed for the skill
3. Get user input if resources require their content (e.g., brand assets)

Update SKILL.md

Critical: Writing Style

Use imperative/infinitive form (verb-first instructions), NOT second person:

❌ Wrong: "You should do X" or "If you need to do X" ✅ Right: "To accomplish X, do Y"

This maintains consistency and clarity for AI consumption.

Questions to answer in SKILL.md:

1. What is the purpose? (Few sentences)

   • Clear, concise explanation of what the skill does

2. When should the skill be used? (Trigger conditions)

   • Specific user queries that should activate the skill
   • Examples of when NOT to use it

3. How should Claude use the skill? (Practical usage)

   • Reference all reusable resources (scripts, references, assets)
   • Explain workflow and decision-making process
   • Include examples of proper usage

Step 5: Packaging the Skill

Purpose: Validate and create a distributable zip file

Command:

scripts/package_skill.py <path/to/skill-folder> [output-directory]

Automatic validation checks:

1. YAML frontmatter format and required fields (name, description)
2. Skill naming conventions and directory structure
3. Description completeness and quality
4. File organization and resource references

Outputs (if validation passes):

• Zip file named after the skill (e.g., my-skill.zip)
• Proper directory structure maintained
• Ready for distribution

Step 6: Iterate

Purpose: Continuous improvement based on real usage

Iteration workflow:

1. Use the skill on real tasks
2. Notice struggles or inefficiencies
3. Identify how SKILL.md or bundled resources should be updated
4. Implement changes and test again

Users often request improvements right after using the skill, when they have fresh context about how it performed.

Best Practices Summary

Based on analyzing skill-creator, here are the key principles for effective skill development:

1. Progressive Disclosure

2. Avoid Duplication

Information should live in either SKILL.md or references files, not both.

• Keep SKILL.md lean with essential procedural instructions
• Move detailed examples, schemas, and reference material to references/
• This keeps core workflow discoverable without context window bloat

3. Imperative Writing Style

Always use verb-first instructions:

❌ Avoid: "You should analyze the user's request" ✅ Use: "Analyze the user's request"

This maintains consistency and clarity for AI consumption.

4. Concrete Examples

Before creating a skill, always gather specific examples:

• "Show me 3 real queries users would ask"
• "What does success look like for each example?"
• "What resources would make repeated execution easier?"

Examples transform abstract requirements into actionable skill contents.

5. Test and Iterate

No skill is perfect on first release:

• Use the skill on real tasks immediately
• Pay attention to where Claude struggles
• Update SKILL.md or resources based on actual usage
• Package and redistribute improved versions

The best skills evolve through real-world testing.

Conclusion

skill-creator embodies the best practices for Claude skill development. By studying its structure and following its 6-step process, you can create skills that:

• ✅ Extend Claude's capabilities systematically
• ✅ Manage context efficiently through progressive disclosure
• ✅ Provide reusable resources for repeated tasks
• ✅ Maintain high quality through validation and iteration
• ✅ Transform Claude from general-purpose to specialized agent

The key insight: Skills are onboarding guides for specific domains. They provide the procedural knowledge that no model can fully possess on its own.

Next Steps

Want to create your own skill? Follow these steps:

1. Clone the skill-creator repository (github.com/anthropics/skills)
2. Run ./scripts/init_skill.py my-skill --path ./my-skills/
3. Follow the 6-step process outlined in this article
4. Package with ./scripts/package_skill.py ./my-skills/my-skill/
5. Test and iterate based on real usage

Additional Resources

• Anthropic Skills Repository: github.com/anthropics/skills
• Creating Your First Skill: /tutorials/creating-first-skill
• Skill Examples Gallery: /development/skill-examples
• Advanced Skill Development: /development/advanced-skills

ℹ️ Source Information

Original Article: skill-creator SKILL.md

• Source: Anthropic Skills Repository
• Author: Anthropic
• Published: 2025-10-16
• Imported: 2025-11-17
• License: Complete terms in LICENSE.txt

This article was automatically processed and translated using Claude AI with defensive content safety measures to prevent MDX syntax errors.